Installation (64-bit linux only)

mkpy is distributed as a conda package for installation into conda virtual environments (see Conda environments). The conda virtual environment and the conda package ecosystem is, at present, the most generally useful approach for cross-platform open-source data analysis. If you don’t yet have conda installed yet, the lightweight miniconda3 (see Miniconda) in combination with the mamba package (see mamba docs) installed in the base environment is strongly recommended.

Note

As of mkpy v0.2.7 the native conda package dependency solver has become unusably slow and unreliable for creating environments and installing packages with many dependencies and packages on conda-forge. As of mkpy v0.2.7, best practices for installation, especially in environments with other Python and R packages are to use mamba with strict conda-forge channel priority.

This version of mkpy is tested with Python 3.7, 3.8, and 3.9 in conda virtual environments constructed as recommended. Other installations, e.g., with conda and different channel priorities may or may not work.

Install the latest stable release

Run these commands in a linux terminal window bash shell with a recent and working conda and mamba executables. The named package channels and their order is important. Replace mkpy_DDMMYY with a sensible environment name. A date string and/or version is not required but may be useful.

To install the latest stable version of mkpy and the most recent versions of the compatible packages including Python in a fresh conda environment:
```
$ mamba create --name mkpy_DDMMYY mkpy -c conda-forge -c defaults -c kutaslab --strict-channel-priority
```

To install mkpy for a specific version of Python, say 3.8:

$ mamba create --name mkpy_DDMMYY python=3.8 mkpy -c conda-forge -c defaults -c kutaslab --strict-channel-priority

To install mkpy into an existing conda environment:

$ conda activate mkpy_DDMMYY
$ mamba install -c conda-forge -c defaults -c kutaslab --strict-channel-priority

Install a pre-release development version

At times an updated development version of mkpy runs ahead of the latest stable release and is available for conda installation. Installing the development version is the same as the release version except for the specification of the channel and label.

$ mamba create --name mkpy_dev_DDMMYY mkpy -c conda-forge -c defaults -c kutaslablabel/pre-release --strict-channel-priority

Note

It strongly recommended to install development versions into a fresh conda environment or risk modifiying an existing working environment in unintended and/or undesireable ways with upgraded or downgraded dependencies.

Install editable source code (development mode)

The default installation puts a frozen snapshot of the mkpy package into the activeenvironment’s site-packages. If you want to modify the mkpy source and have the changes show up when you import the package and call the methods you can install in “development mode”.

Best practices are to first use mamba create to create a new conda development environment populated with the latest mkpy release, cython, and mkpy dependencies. Then activate the environment and run pip install -e . to install mkpy in “development” mode which replaces the downloaded conda package in the Python site-packages/mkpy directory with a link to your souce code directory.

First, navigate to the working directory where you plan to edit mkpy.

$ mamba create --name mkpy_dev_DDMMYY \
    mkpy cython \
    -c conda-forge -c defaults -c kutaslablabel/pre-release \
    --strict-channel-priority
$ conda activate mkpy_dev_DDMMYY
$ git clone https://github.com/kutaslab/mkpy --branch dev --single-branch
$ cd mkpy
$ pip install . -e